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Lidar Annotation for Machine Learning

The customer observed a threefold increase in model performance using a smaller dataset for 3D Cuboids on LiDAR Clouds

Industry and use case:

Robotics

Data:

2,000 LiDAR clouds

Project duration:

12 days

Our Challenge:

A pioneering developer sought a high-quality annotated dataset comprising LiDAR clouds extracted from real city streets to enhance a neural network’s spatial orientation and object distance determination

Our Solution:

We conducted the annotation using tools such as Supervisely and SUStechPOINTS. To ensure data quality, annotators marked the most challenging images, facilitating subsequent discussions and collective decisions on object selection accuracy

Outcomes:

Achieved 99% accuracy in the dataset.

The customer observed a threefold increase in model performance using a smaller dataset.

"Lidar annotations are among the most intricate. The team assembled for our project worked seamlessly, producing top-tier data in under 2 weeks, significantly enhancing the neural network's performance"
Vladislav B.
Chief Data Scientist

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Robotics

Annotate 3D models and LIDAR points to assist robots in preventing crashes through object detection

Stages of work

  • Application

    /01
    Leave a request on the website for a free consultation with an expert. Th e acco unt manager will guide you on the services, timelines, and price

  • Free pilot

    /02
    We will conduct a test pilot project for you and provide a golden set, based on which we will determine the final technical requirements and approve project metrics

  • Agreement

    /03
    We prepare a contract and all necessary documentation upon the request of your accountants and lawyers

  • Workflow customization

    /04
    We form a pool of suitable tools and assign an experienced manager who will be in touch with you regarding all project details

  • Quality control

    /05
    Data uploads for verification are done iteratively, allowing your team to review and approve collected/annotated data

  • Post-payment

    /06
    You pay for the work after receiving the data in agreed quality and quantity

Timeline

  • 24 hours
    Application
  • 24 hours
    Consultation
  • 1 to 3 days
    Pilot
  • 1 to 5 days
    Conducting a pilot
  • 1 day to several years
    Carrying out work on the project
  • 1 to 5 days
    Quality control
You pay for the work after you have received the data
in the established quality and quantity

Why
Training Data

  • Quality Assurance:
  • Enhanced Data Accuracy
  • Consistency in Labels
  • Reliable Ground Truth
  • Mitigation of Annotation Biases
  • Cost and Time Efficiency
  • Data Security and Confidentiality:
  • GDPR Compliance
  • Non-disclosure agreement
  • Data Encryption
  • Multiple data storage options
  • Access Controls and Authentication
  • Expert Team:
  • 6 years in industry
  • 35 top project managers
  • 40+ languages
  • 100+ countries
  • 250k+ assessors
  • Flexible and Scalable Solutions:
  • 24/7 availability of customer service
  • 100% post payment
  • $550 minimum check
  • Variable Workload
  • Customized Solutions
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Tell us about your project!

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    Select an option

    • Data labeling

    • Data collection

    • Datasets

    • Human Moderation

    • Other (describe below)